The Maximum Hail Size Assessment Regression Model by Predictive Fields of Meteorological Parameters

The need to develop new methods for predicting the characteristics of hail processes is dictated, on the one hand, by the trend of growth of convective dangerous weather events due to climate change, on the other hand, by the lack of actual data of aerological sounding due to the location of individual weather stations far enough from each other and the existence of a significant time interval of measurements. In this research instead of upper-air atmospheric sounding data, it is proposed to use the output of the GFS NCEP global atmospheric model, which has sufficient accuracy and the required lead time. The size of the hail is considered as a quantitative characteristic of the hail process. The hail assessment regression model was implemented using statistical analysis methods based on pre-calculated atmospheric parameters that are most responsible for the development of convective phenomena. The model parameters characterizing the statistical significance and practical applicability of the model showed the possibility of applying the proposed model in practice.